Drought Assessment with the Community Land Model for 1951–2010 in East Asia

Myoung-Jin Um,Daeryong Park,Yeonjoo Kim,Mun Kim

doi:10.3390/su10062100

Myoung-Jin Um, Daeryong Park + Show 2 more

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https://doi.org/10.3390/su10062100

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Journal: Sustainability	Publication Date: Jun 20, 2018
Citations: 6	License type: CC BY 4.0

Affiliation: Yonsei University, Konkuk University, Shingu College

Abstract

Severe droughts have occurred in East Asia; however, observational hydroclimate data that covers the entire region is lacking. The objective of this study is to investigate drought assessment in East Asia. This study estimated three drought indices by generating hydroclimate variables using the Community Land Model (CLM). The results of the CLM were verified by comparison with Climatic Research Unit (CRU) data for precipitation and air temperature and the Global Runoff Data Centre (GRDC) data for runoff. Spatial and temporal variations in three drought severity indices, including the standardized precipitation evapotranspiration index (SPEI), the standardized runoff index (SRI), and the Standardized Soil Moisture Index (SSMI), in East Asia were estimated using the CLM output and compared with the SPEI in the CRU. This study classified drought frequency into four classes depending on the drought severity with 5-deg gapped longitude and latitude for 1951–2010 in East Asia and found that moderately dry (D2) and severely dry (D3) drought frequency classes matched well between the CLM and CRU data. The SPEI in the CLM and CRU data showed very similar frequency magnitudes and an increasing temporal trend. The SRI and SSMI frequencies for CLM also showed an increasing temporal trend compared to the SPEI frequency trend. The results of this study show that CLM outputs are reliable for drought analysis in East Asia. Furthermore, this study suggests the possibility of CLM application to other regions to generate hydroclimate data that is otherwise insufficient.

Highlights

A drought is defined as a period in which a particular variable, such as precipitation, soil water, or runoff amounts, exhibits lower-than-average levels in a specific region, resulting in widespread economic, environmental, and social impacts [1,2,3]
The Climatic Research Unit (CRU) dataset is the combination of many datasets from sources such as the World Meteorological Organization (WMO) and the United States National Oceanographic and Atmospheric Administration (NOAA, via its National Climatic Data Center, NCDC); it is constructed by the climate anomaly method (CAM) [38]
This study quantified the accuracy of the Community Land Model (CLM) in predicting the observed meteorological drought data and investigated the propagation of meteorological droughts in the CLM to hydrological and agricultural droughts for 1951–2010 in East Asia

Summary

Introduction

A drought is defined as a period in which a particular variable, such as precipitation, soil water, or runoff amounts, exhibits lower-than-average levels in a specific region, resulting in widespread economic, environmental, and social impacts [1,2,3]. The standardized precipitation index (SPI) [4,5] calculates the normalized long-term precipitation to evaluate the class of droughts. Vicente-Serrano et al [6] suggested the standardized precipitation evapotranspiration index (SPEI), which is calculated using a combination of the water balance and cumulative water deficit and the adjusted log-logistic probability distribution [7]. The standardized runoff index (SRI) is used to express hydrological droughts [8] and requires runoff datasets. A standardized soil water index (SSWI) was suggested. Both SRI and SSWI have been applied to droughts in the United States with the SWAT model [9] and in China with the Variable Infiltration Capacity (VIC) model [10]

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